{"as_of":"2026-08-08T07:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0796bcc3385b1aef4ed96e7c8ecdf3872e360f5395587441e51bd99b6ee5c645","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:16:00.742122Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-13T07:27:29.797670Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-07T04:16:00.742122Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11347","last_updated":"2025-07-20T00:54:08Z","snapshot_observed_at":"2026-08-07T04:08:31.219713Z","submitted_at":"2025-06-12T22:47:21Z","title":"Improving Group Robustness on Spurious Correlation via Evidential Alignment","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:16:00.742122Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2506.11347"},"observation_digest":"sha256:d8c7a55f2c7b49d126ca1ae6a3a24d3c46dc94cb4f7c1d3ac60e60602da17dab","observation_id":"d14a0e0a-551f-4b8c-b905-e371f3f92139","resolution":{"observed_at":"2026-08-07T04:16:00.742122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-06T15:19:03.147374Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.16219","last_updated":"2025-07-22T04:29:53Z","snapshot_observed_at":"2026-08-06T19:31:58.667264Z","submitted_at":"2025-07-22T04:29:53Z","title":"Bayesian Deep Learning for Convective Initiation Nowcasting Uncertainty Estimation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T15:19:03.147374Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2507.16219"},"observation_digest":"sha256:862e23a24e622a3d35a66208c178753d12fdccffa261ff67f6ba998f7e4778e3","observation_id":"8d802a68-ad92-471d-b240-ae0c78843f34","resolution":{"observed_at":"2026-08-06T15:19:03.147374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-05T19:29:00.979735Z","title":"Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estima- tion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.12464","last_updated":"2025-08-17T18:27:54Z","snapshot_observed_at":"2026-08-06T19:31:58.152011Z","submitted_at":"2025-08-17T18:27:54Z","title":"On the Fitness Landscape in the $NK$ Model","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-05T19:29:00.979735Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2508.12464"},"observation_digest":"sha256:82adb4001fc1b655b990fb5b339f41d8fc3d7f97fa5fc70c1ec3b2c1bf2fe67b","observation_id":"9cacb826-2b11-4a98-a8fe-18037959b7c0","resolution":{"observed_at":"2026-08-05T19:29:00.979735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-04T20:59:55.782690Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.08280","last_updated":"2025-09-10T04:37:00Z","snapshot_observed_at":"2026-08-04T20:59:53.301349Z","submitted_at":"2025-09-10T04:37:00Z","title":"Generalized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-04T20:59:55.782690Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2509.08280"},"observation_digest":"sha256:8d9e033da66f47712d2af35d649ed3ee8369d35099763879e848b46369dd837f","observation_id":"1cd4fd00-9c3e-4a31-ba5e-36494c032105","resolution":{"observed_at":"2026-08-04T20:59:55.782690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-03T05:43:50.528165Z","title":"Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estimation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.01477","last_updated":"2026-07-17T13:59:21Z","snapshot_observed_at":"2026-08-06T03:21:25.071799Z","submitted_at":"2026-02-01T22:57:39Z","title":"Density-Informed Pseudo-Counts for Calibrated Evidential Deep Learning","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T05:43:50.528165Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2602.01477"},"observation_digest":"sha256:92758cdef39f75641c8652584ce85f560a1dc93bb77bf438d025fea278926778","observation_id":"f2cca48b-e092-4ebf-bc66-80969d6931d3","resolution":{"observed_at":"2026-08-03T05:43:50.528165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":"2110.03051","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estima- tion","venue":null,"work_id":"4bc4aaae-3123-4353-9397-e9372b242df9","year":2021},"citing_paper":{"arxiv_id":"2604.06032","last_updated":"2026-04-07T16:28:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-07T16:28:20Z","title":"Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T18:38:30.129473Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2604.06032"},"observation_digest":"sha256:e88c6122804ec2f3ac88380e2577aeb31d74f5aedcecb21888bd52a84512848e","observation_id":"fc7c692c-32d8-42e1-90ea-88b1e4b3cf7e","resolution":{"observed_at":"2026-05-11T00:15:51.948343Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":"2110.03051","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estima- tion","venue":null,"work_id":"4bc4aaae-3123-4353-9397-e9372b242df9","year":2021},"citing_paper":{"arxiv_id":"2605.10378","last_updated":"2026-07-29T20:31:21Z","snapshot_observed_at":"2026-08-02T23:16:55.232500Z","submitted_at":"2026-05-11T11:21:49Z","title":"Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-12T04:04:30.271351Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2605.10378"},"observation_digest":"sha256:9061626c0d624652656aa206b6623f6dfd5d58a1f1a9ef5c7d9c9d75242d0ffe","observation_id":"9a3079ec-44ed-4bb1-9c7b-f96a745c3276","resolution":{"observed_at":"2026-05-12T06:41:32.766874Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-08-02T14:26:27.999137Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2605.10378","last_updated":"2026-07-29T20:31:21Z","snapshot_observed_at":"2026-08-02T23:16:55.232500Z","submitted_at":"2026-05-11T11:21:49Z","title":"Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation","version":2},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-02T14:26:27.999137Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2605.10378"},"observation_digest":"sha256:e44ea036b887d6dd61fe6ad0c98c8cd2568d2c7a1d4777ec1867100cb67d007e","observation_id":"4ec275e6-775b-44fe-944b-7d2040406ecd","resolution":{"observed_at":"2026-08-02T14:26:27.999137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation","version":3},"cited_work":{"arxiv_id":"2110.03051","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.03051","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estima- tion","venue":null,"work_id":"4bc4aaae-3123-4353-9397-e9372b242df9","year":2021},"citing_paper":{"arxiv_id":"2605.10984","last_updated":"2026-05-09T05:17:20Z","snapshot_observed_at":"2026-08-07T12:56:04.950554Z","submitted_at":"2026-05-09T05:17:20Z","title":"Principle-Guided Supervision for Interpretable Uncertainty in Medical Image Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-13T07:25:51.521656Z"},"links":{"cited_paper":"/paper/2110.03051","citing_paper":"/paper/2605.10984"},"observation_digest":"sha256:309e6ee63ff33a1c4a939323ecb5bb9030b37677b8053ddcb254f7b6b28f001a","observation_id":"aacaeaee-5ca1-4064-974e-de88a0d01328","resolution":{"observed_at":"2026-05-13T07:27:29.800680Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2110.03051/citation-record","integrity":"/paper/2110.03051/integrity","json":"/paper/2110.03051/citation-record.json","paper":"/paper/2110.03051"},"outbound":[],"paper":{"arxiv_id":"2110.03051","last_updated":"2023-03-07T18:05:45Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T18:59:43.510907Z","submitted_at":"2021-10-06T20:13:57Z","title":"Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2110.03051."}